Italian validation of the Sleep Condition Indicator: A clinical screening tool to evaluate Insomnia Disorder according to DSM-5 criteria

Abstract Background Epidemiological studies of insomnia in the Middle East remain scarce. The present study aimed to estimate the prevalence of insomnia and explore its associations in the general population of Qatar. With almost 100 nationalities, Qatar is one of the most culturally diverse, richest, and fastest developing countries in the Arabian Peninsula. Methods A probability sample of community-dwelling adults were surveyed in February of 2019. A total of 1611 respondents completed face-to-face interviews in Arabic or English. Logistic regression modeled associations with insomnia, our dependent variable, as defined by a score of ≤16 on the eight-item Sleep Condition Indicator or according to criteria for insomnia in the Diagnostic & Statistical Manual of Mental Disorders, fifth edition or DSM-5. Results Approximately, 5.5% of the sample screened positive for insomnia and the 30-day prevalence of those who met all the DSM-5 criteria for insomnia disorder was 3.0%. In addition, 2.0% of the sample screened positive for depression and 3.4% for anxiety in the past 2 weeks. Multivariable analysis showed the following were significantly associated with insomnia: Arab ethnicity, young age, unemployment, being married, having less than high school education, fair or poor health, anxiety, and depression. Conclusions Insomnia prevalence was in the lower range of previously reported DSM-defined estimates from developed Western countries. Our findings highlight the need for raising awareness and improving sleep hygiene in potential risk groups such as younger adults and those of Arab ethnicity, in addition to incorporating insomnia screening in the provision of mental health services.

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Diagnostic Validity of the Sleep Condition Indicator to Screen for Diagnostic and Statistical Manual-5 Insomnia Disorder in Patients with Parkinson’s Disease

European Neurology ◽

10.1159/000508185 ◽

2021 ◽

pp. 1-7

Author(s):

Sophie Bayard ◽

Cindy Lebrun ◽

Alexia Arifi-Rossignol ◽

Christian Geny ◽

Marie-Christine Gély-Nargeot ◽

...

Keyword(s):

Parkinson’S Disease ◽

Factor Analysis ◽

Clinical Interview ◽

Divergent Validity ◽

Statistical Manual ◽

Diagnostic And Statistical Manual ◽

Dsm 5 ◽

Insomnia Disorder ◽

Sleep Condition ◽

Condition Indicator

Background: Insomnia is a highly common sleep disorder in patients with Parkinson’s disease (PD). Yet, no screening questionnaires following the Diagnostic and Statistical Manual-5 (DSM-5) criteria have been validated in PD patients. Objectives: We assessed the validity and reliability of the French version of the sleep condition indicator (SCI), in patients with PD. Methods: In a sample of 65 patients (46% women, mean age 63.8 ± 7.9 years) with PD, but without dementia, insomnia was assessed with a clinical interview and the SCI. Statistical analyses were performed to determine the reliability, construct validity, and divergent validity of the SCI. In addition, an explanatory factor analysis was performed to assess the underlying structure of the SCI. Results: Of the 65 patients (mean duration PD 9.7 ± 6.9 years), 51% met the criteria for insomnia disorder when measured with a clinical interview. The mean SCI score was 18.05 ± 8.3. The internal consistency (α = 0.89) of the SCI was high. Using the previously defined cutoff value of ≤16, the area under the receiver operating characteristic curve was 0.86 with a sensitivity of 86% and a specificity of 87%. Exploratory factor analysis showed a 2-factor structure with a focus on sleep and daytime effects. Additionally, good construct and divergent validity were demonstrated. Conclusion: The SCI can be used as a valid and reliable screener for DSM-5 insomnia disorder in PD patients. Due to its short length, it is useful in both clinical practice and scientific research.

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The association between Insomnia Disorder and Depression in the General Population of Qatar: The Role of Inflammatory Disease

University of the Future: Re-Imagining Research and Higher Education ◽

10.29117/quarfe.2020.0131 ◽

2020 ◽

Author(s):

Salma Mawfek Khaled ◽

Catalina Gabriela Petcu ◽

Maryam Ali Al-Thani ◽

Aisha Mohammed Al-Hamadi ◽

Peter Woodruff

Keyword(s):

Major Depression ◽

Inflammatory Disease ◽

Computer Assisted ◽

Healthy Population ◽

Insomnia Disorder ◽

Sleep Condition ◽

Inflammatory Processes ◽

History Of ◽

Condition Indicator

Background: There is emerging evidence that supports a role for inflammatory processes and insomnia in the pathophysiology of depression. However, little is known about the role of inflammation in depression and insomnia in non-clinical populations. Aims: We aimed to estimate the association between inflammatory illness, depression and insomnia in the Qatari population. We hypothesized that inflammatory illness would be associated with sub-clinical depression and insomnia in the Qatari population. Methods: We used probability-based sampling on a representative sample (N= 1,611) of Qatar’s adult household population. Face-to-face interviews were conducted using computer-assisted technology as part of the SESRI’s annual omnibus survey in 2019. We used the Espie’s (2014) Sleep Condition Indicator, to assess insomnia symptoms, and PHQ-9 and GAD-2 for subthreshold depression (SUBD), major depressive disorder (MDD), and anxiety. Health information including personal and family history of inflammatory disease were also collected. Univariate, bivariate, and multivariate statistics were conducted. Results: Among those with no inflammatory disease, the 30-day prevalence of subthreshold and major depression in those with insomnia disorder compared to those without insomnia was (SUBD: 5.3% vs 2.9%; MDD: 7.2% vs 0.6%, P<0.001), respectively. In contrast, among respondents with inflammatory disease, the prevalence of subthreshold and major depression in those with insomnia compared to those without insomnia was (SUBD: 11.8% vs 3.6%; MDD: 17% vs 1.7%, P<0.001), respectively. In crude (adjusted for age, gender, and household type) models with depression as a dependent variable, a statistically significant association between SUBD and insomnia was found (OR=4.2, P<0.01), while much stronger association was found between major depression and insomnia (OR=20.4, P<0.001). Conclusion: These findings highlight the possible impact of inflammatory disease on mental health in the otherwise healthy population of Qatar.

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Psychometric properties of the Sleep Condition Indicator and Insomnia Severity Index in the evaluation of insomnia disorder

Sleep Medicine ◽

10.1016/j.sleep.2016.05.019 ◽

2017 ◽

Vol 33 ◽

pp. 76-81 ◽

Cited By ~ 24

Author(s):

Mark Lawrence Wong ◽

Kristy Nga Ting Lau ◽

Colin A. Espie ◽

Annemarie I. Luik ◽

Simon D. Kyle ◽

...

Keyword(s):

Psychometric Properties ◽

Severity Index ◽

Insomnia Severity Index ◽

Insomnia Disorder ◽

Sleep Condition ◽

Condition Indicator ◽

Insomnia Severity

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Development of a Clinical Screening Tool for Undiagnosed Diabetes in a Hospital Observation Unit

Diabetes ◽

10.2337/db18-1323-p ◽

2018 ◽

Vol 67 (Supplement 1) ◽

pp. 1323-P

Author(s):

REBECCA M. NOONAN ◽

WILFRIDO J. CASTILLO ◽

GABRIEL M. SAFFRAN ◽

COLLIN B. MONTGOMERY ◽

GANESH PHAYAL ◽

...

Keyword(s):

Screening Tool ◽

Undiagnosed Diabetes ◽

Observation Unit ◽

Clinical Screening

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Psychometric Properties of a DSM-5-Based Screening Tool for Women's Perceptions of Premenstrual Symptoms

Psychological Reports ◽

10.1177/0033294120979696 ◽

2021 ◽

pp. 003329412097969

Author(s):

Meghan A. Richards ◽

Kirsten A. Oinonen

Keyword(s):

Psychometric Properties ◽

Screening Tool ◽

Physical Symptoms ◽

Premenstrual Symptom ◽

Future Research ◽

Premenstrual Symptoms ◽

Screening Measure ◽

Dsm 5 ◽

Symptom Screening ◽

Women’S Perceptions

A premenstrual screening tool is needed when time constraints and attrition limit the feasibility of daily ratings. The present study examines the utility of a novel, 33-item, retrospective, dimensional, DSM-5-based, screening measure developed to explore women’s perceptions of premenstrual symptomatology. This is the first measure that examines perception of impairment for each DSM-5 symptom and assesses the frequency criterion. Participants (N = 331) reported symptoms ranging from none to a level consistent with a provisional DSM-5 diagnosis of Premenstrual Dysphoric Disorder (PMDD). Initial psychometric properties indicated a five-factor structure: (1) affective symptoms; (2) fatigue, sleep, and anhedonia; (3) symptom frequency; (4) impairment and severity of appetite change and physical symptoms; and (5) difficulty concentrating. The total symptom scale and the frequency, severity, and impairment subscales demonstrated high internal consistency. Strong correlations between this dimensional measure and other retrospective and prospective premenstrual symptom measures suggest strong convergent, concurrent, and predictive validity. Premenstrual symptom groups created using this screening measure (minimal, mild/moderate, severe) differed on other retrospective and prospective measures of premenstrual symptoms. There was evidence of divergent validity and lack of an acquiescence bias. We also report data describing women’s perceptions of the frequency, level of impairment, and level of severity for each DSM-5 PMDD symptom over a 12-month period and discuss implications for future research on premenstrual phenomenology. Initial evidence for the reliability and construct validity of this symptom screening measure suggests potential value for assessing premenstrual symptomatology in research and practice.

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Digital cognitive behaviour therapy for insomnia (CBTi) for adolescents with mental health problems. Results from a feasibility open trial. (Preprint)

10.2196/preprints.14842 ◽

2019 ◽

Author(s):

Bethany Cliffe ◽

Abigail Croker ◽

Megan Denne ◽

Jacqueline Smith ◽

Paul Stallard

Keyword(s):

Mental Health ◽

Mental Health Services ◽

Health Services ◽

Mental Health Problems ◽

Health Problems ◽

Anxiety And Depression ◽

Severity Scale ◽

Sleep Condition ◽

Condition Indicator ◽

Insomnia Severity

BACKGROUND Insomnia in adolescents is common, persistent, and associated with poor mental health including anxiety and depression. Insomnia in adolescents attending child mental health services is seldom directly treated and the effects of digital CBTi on the mental health of adolescents with significant mental health problems is unknown. OBJECTIVE This paper reports an open study assessing the feasibility of adding supported online CBT for insomnia to the usual care of young people aged 14-17 years attending specialist child and adolescent mental health services. METHODS Thirty-nine adolescents aged 14-17 attending specialist child and adolescent mental health services with insomnia were assessed and offered digital CBTi. The digital intervention was Sleepio, an evidence based, self-directed, fully automated CBTi that has proven effective in multiple randomized controlled trials with adults. Self-report assessments of sleep (Sleep Condition Indicator, Insomnia Severity Scale, online sleep diaries), anxiety (Revised Child Anxiety and Depression Scale) and depression (Mood and Feelings Questionnaire) were completed at baseline and post-intervention. Post-use interviews assessed satisfaction with digital CBTi. RESULTS Average baseline sleep efficiency was very poor (52.9%) with participants spending an average of 9.6 hrs in bed but only 5.1 hrs asleep. All scored <17 on the Sleep Condition Indicator with 36/39 (92.3%) scoring ≥15 on the Insomnia Severity Scale, suggesting clinical insomnia. 36 (92.3%) scored ≥ 27 on the Mood and Feelings Questionnaire for major depression and 20 (51.3%) had clinically elevated symptoms of anxiety. The majority (76%) were not having any treatment for their insomnia, with the remaining 24% receiving medication. Sleepio was acceptable with 77% (30/39) activating their account and 67% (21/30) completing the program. Statistically significant pre-post improvements were found in weekly diaries of sleep efficiency (p=.005) and sleep quality (p=.001) and on measures of sleep (SCI; p=.001: ISI; p=.001), low mood (MFQ; p=.024) and anxiety (RCADS; p=.015). Satisfaction was high; with 89% finding Sleepio helpful, 94% would recommend it to a friend with 39% expressing a definite preference for a digital intervention. CONCLUSIONS Our study has a number of methodological limitations, particularly the small sample size, absence of a comparison group and follow-up assessment. Nonetheless, our findings are encouraging and suggest that digital CBTi for young people with mental health problems might offer an acceptable and an effective way to improve both sleep and mental health. CLINICALTRIAL N/a

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